Session
Tenth International Workshop on Heterogeneous High-performance Reconfigurable Computing (H2RC '24)
Session Chairs
DescriptionAs conventional von-Neumann architectures are suffering from rising power densities, we are facing an era with power, energy efficiency, and cooling as first-class constraints for scalable HPC. FPGAs can tailor the hardware to the application, avoiding overheads and achieving higher hardware efficiency than general-purpose architectures. Leading FPGA manufacturers have made a concerted effort to provide a range of higher-level, easier-to-use high-level programming models for FPGAs, and much of the work in FPGA-based deep learning is built on these frameworks. Such initiatives are already stimulating new interest within the HPC community around the potential advantages of FPGAs over other architectures. With this in mind, this workshop, now in its tenth year, brings together HPC and heterogeneous-computing researchers to demonstrate and share experiences on how newly-available high-level programming models, are already empowering HPC software developers to directly leverage FPGAs, and to identify future opportunities and needs for research in this area.
Event TypeWorkshop
TimeFriday, 22 November 20248:30am - 12pm EST
LocationB208
Embedded and/or Reconfigurable Systems
Heterogeneous Computing
W
Presentations
8:30am - 8:35am EST | H2RC '24 Opening Remarks Presenter | |
8:35am - 9:20am EST | HPC on a Reconfigurable Substrate with Machine Learning Support Presenter | |
9:20am - 9:40am EST | Lowering the Barriers to Programming FPGAs and AIEs for HPC Presenter | |
9:40am - 10:00am EST | What Should be Used for Reconfigurable HPC, FPGA or Coarser-Grain Reconfigurable Architecture? Presenter | |
10:00am - 10:30am EST | H2RC '24 — Morning Break | |
10:30am - 11:00am EST | ProTEA: Programmable Transformer Encoder Acceleration on FPGA | |
11:00am - 11:30am EST | DeLiBA-K: Speeding-up Hardware-Accelerated Distributed Storage Access by Tighter Linux Kernel Integration and Use of Modern API | |
11:30am - 11:45am EST | Developing a BLAS library for the AMD AI Engine | |
11:45am - 12:00pm EST | AMD University Program Overview Session Chair |